How fees and slippage destroy trading bot ROI, with real numbers

Key takeaways

1. 1Every automated round trip pays two fees plus slippage both ways; that cost repeats on every trade.
2. 2A 0.14% round trip compounds to roughly -75% over 1,000 trades for a strategy with no edge.
3. 3Most tournament strategies that look profitable gross lose net because they trade too often.
4. 4Book results from exchange fills with real fees, and judge every setup on net ROI after costs.

The round trip

Every automated trade pays at least twice: a fee to enter and a fee to exit. Most bot entries and exits are market orders, which pay the higher taker rate and cross the spread, so slippage adds more. Together that is the round-trip cost. It sounds small, a few hundredths of a percent, but it is paid on every trade, and bots make many trades.

How small costs compound

Our analysis of TradingView strategies in the script tournament shows the arithmetic plainly. A round-trip cost of 14 basis points (0.14%) compounds to about minus 75% over 1,000 trades for a strategy with no edge. One strategy that looked like plus 6.2% gross became minus 98.4% net over 3,012 trades. The large mass of tournament strategies between minus 50% and minus 80% is not bad luck; it is fee drag on scripts that trade too often for their edge.

0.14% round trip × 1,000 trades

about -75% with no edge

+6.2% gross, 3,012 trades

-98.4% net

our optimizer cost model

5 bps fee + 2 bps slippage per side

Real books: gross vs net

The live widget below shows TensorTrader's Binance testnet TT-Autotune book. Across more than 4,300 closed trades, gross profit hovers near zero while cumulative fees climb steadily, so net ROI drifts negative. It is the most honest chart we can show: the strategy roughly breaks even before costs, and costs decide the outcome.

Count costs the way the exchange does

Many dashboards compute profit from entry and exit prices and forget the fees. TensorTrader books closed trades from the exchange's own fills: realized profit comes from the venue's fill records and the fee is the venue-reported round trip, already subtracted from net profit. An earlier price-formula approach under-reported venue losses by about four times, which is why every live-ready venue must pass fill-based close booking before it goes live.

How to fight fee drag

1. 1Trade less: higher timeframes and stricter conditions fire fewer, better alerts.
2. 2Demand a bigger edge per trade: if expected profit per trade is under twice the round-trip cost, skip it.
3. 3Use exchange fee tiers and maker orders where your strategy allows.
4. 4Avoid thin markets where slippage is large.
5. 5Judge every setup on net results after fees, on paper, over hundreds of trades.

A quick calculator

Plug in your own numbers. With a 0.05% taker fee and 0.02% slippage each way, the round trip is 0.14%. A strategy that trades 50 times a week on 500 USD of notional pays about 35 USD a week in costs. If your paper results show less than that in gross profit, the strategy cannot survive live.

round_trip_cost = 2 * taker_fee + 2 * slippage
break_even_edge = round_trip_cost per trade
weekly_cost     = trades_per_week * notional * round_trip_cost

Frequently asked questions

What is a good round-trip cost?

As low as possible; for frequent strategies even 0.1% per round trip is a large hurdle.

Does TensorTrader show fees per trade?

Yes. Closed trades carry the venue-reported fee and net profit.

Are maker orders always cheaper?

Usually, but they may not fill. Strategies that need to be in the market on a signal mostly pay taker rates.

Does slippage matter on liquid markets?

Less, but it never disappears; it grows with order size and in fast markets.

Do fees change with leverage?

Fees are charged on notional, so at higher leverage the same margin pays proportionally more in fees.

Keep reading

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• Best timeframes for automated Hyperliquid perps: what the optimizer found

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